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Quantitative X-ray determination of mineral content by RIETVELD-based techniques is a powerful method for analysing complex mineral mixtures. For montmorillonite the use of this method is excluded due to the lack of a proposed structure model. This lack is a direct consequence of the disordered, semi-crystalline nature of this mineral. Nevertheless, a lot is known about individual parts of the structure.
In recent years, computer modeling techniques based on quantum mechanics and energy minimisation have provided additional and confirmative information to the picture of the interlayer structure established by experimental techniques such as X-ray and spectroscopic analysis.
In the present study, a structure model for collapsed, potassium exchanged montmorillonite  was expanded to the interlayer distances of one- and two-layer hydrated montmorillonite (d001 = 12.4 Å resp. d001 = 15.2 Å). In order to simulate an ideal model, the monoclinic angle ß was adjusted. The line between two adjacent hydroxyl oxygens of neighboring clay sheets was assumed to be perpendicular to the sheets in the ideal model as it may be approximated for non-expandable 2:1 layer silicates.
The interlayer structure for sodium and calcium montmorillonite was simulated for different relative humidities by the Monte Carlo simulations . Crystal coordinates for the position of the interlayer cations and the oxygens of the water molecules were extracted and implemented into the expanded structure model.
Quantification calculations were performed using the software AUTOQUANÓ for different size fractions of the Wyoming bentonite "Volclay". The results were judged by the Rwp-value, the Durbin-Watson statistics  and calibration measurements. For calibration purposes, calculated montmorillonite, quartz and feldspar contents of different size fractions were compared to contents estimated on the basis of chemical analysis. Additionally, reference mixtures with added quartz were prepared, analysed and results checked for consistency. The results look promising and the potential for development by implementing real order models is high .
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